TY - JOUR
T1 - Knowledge Engineering with Big Data (BigKE)
T2 - A 54-Month, 45-Million RMB, 15-Institution National Grand Project
AU - Wu, Xindong
AU - Chen, Huanhuan
AU - Liu, Jun
AU - Wu, Gongqing
AU - Lu, Ruqian
AU - Zheng, Nanning
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2017/6/14
Y1 - 2017/6/14
N2 - Starting in July 2016, the Ministry of Science and Technology of China, along with several other national agencies, sponsors a 54-month 45-million RMB (Chinese Yuan) project on knowledge engineering with Big Data (www.bigke.org) for 15 top research and development institutions to study the fundamental theory and the applications of BigKE, a big-data knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation. The project seeks to provide petabyte-scale data and knowledge services in identified application domains. In this paper, we discuss our BigKE framework, and present a novel application scenario for BigKE services.
AB - Starting in July 2016, the Ministry of Science and Technology of China, along with several other national agencies, sponsors a 54-month 45-million RMB (Chinese Yuan) project on knowledge engineering with Big Data (www.bigke.org) for 15 top research and development institutions to study the fundamental theory and the applications of BigKE, a big-data knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation. The project seeks to provide petabyte-scale data and knowledge services in identified application domains. In this paper, we discuss our BigKE framework, and present a novel application scenario for BigKE services.
KW - Knowledge engineering
KW - data mining
UR - https://www.scopus.com/pages/publications/85021752711
U2 - 10.1109/ACCESS.2017.2710298
DO - 10.1109/ACCESS.2017.2710298
M3 - 文章
AN - SCOPUS:85021752711
SN - 2169-3536
VL - 5
SP - 12696
EP - 12701
JO - IEEE Access
JF - IEEE Access
M1 - 7948800
ER -